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Copado Brings AI Agents to DevOps Platform for Building Custom Salesforce Apps

Copado has added artificial intelligence (AI) agents to its DevOps platform for building and deploying custom applications for the software-as-a-service (SaaS) application platform from Salesforce.

At launch, Copado is making available Agentia AI agents specifically that can be assigned plan, build and testing tasks via an orchestration agent that manages the overall workflow. Each Agentia AI agent understands the unique metadata framework that Salesforce developed but also all the dependencies, pipelines and testing activity occurring across the software development lifecycle (SDLC) that is captured via the Agentia Context Hub.

Additionally, there is an Agentia Studio tool that can be used to build AI workflows and other autonomous agents.

Copado CEO Ted Elliot said the Agentia AI agents have been trained using metadata, pipelines, and customer-provided knowledge to automate, for example, planning and documentation tasks or the actual writing for code.

DevOps teams can also apply policy-based controls based on roles and approval gates. Those teams can also generate a complete audit trail for any agentic workflow that is executed.

Finally, Copado plans to soon provide additional observability agents to provide deeper levels of visibility across the SDLC.

The overall goal is to increase the speed at which applications can be developed in a way that also serves to improve quality, said Elliot. While application development tools can use any number of AI coding tools, if they lack any context about the runtime environment the quality of that code is always going to be suboptimal, he added.

AI tools, ultimately, should be used to augment human application developers that can now spend more time building applications that provide more value to the organization, noted Elliot.

However, if application developers are removed from that process organizations will one day discover they will need to retrain them because ultimately it’s a human that is responsible for how any given application functions, he added. Application developers, even with the help of AI, are not going to be able to fix code if they don’t understand how it was constructed in the first place, noted Elliot.

Mitch Ashley, vice president and practice lead for software lifecycle engineering at the Futurum Group, said DevOps teams have a clear need for agentic SDLC platforms that, in addition to enabling them to govern agents, also allow them to prove what shipped. Multiple vendors are competing to own the agent control plane within a Salesforce environment, he added.

Regardless of approach, the pace at which custom Salesforce applications can be built and deployed has accelerated. It’s not clear how many of the organizations building those applications have an appreciation for best DevOps practices, but as the number of applications that need to be maintained increases, the need for a more structured approach to application development becomes apparent.

The challenge then, of course, becomes integrating custom Salesforce applications with the rest of the portfolio of applications that is being managed by all the other DevOps teams that typically exist in the same organization.



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